SEARCH · Engineering Papers

Results for “model base engineering”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 865 records · Page 48

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Techno-economic performances and life cycle greenhouse gas emissions of various ammonia production pathways including conventional, carbon-capturing, nuclear-powered, and renewable production

Ammonia (NH 3 ) is conventionally produced using fossil natural gas (NG) for hydrogen production through steam reformation and synthesis in the Haber–Bosch (HB) process. The global conventional ammonia production contributes more than 420 million tons of CO 2 emissions annually. Here, in this work, we investigated the techno-economics and well-to-plant-gate (WTG) greenhouse gas (GHG) emissions of conventional NG-based, carbon-capturing, nuclear-powered, and renewable ammonia production by developing an engineering process model for each. Carbon-capturing ammonia production refers to the NG-based ammonia production while capturing CO 2 and transporting it via pipelines for storage or utilization. Nuclear-powered and renewable ammonia production represents an alternative ammonia production through water electrolysis, air separation, and the HB process using carbon-free energy sources. Nuclear and renewable energy sources are assumed to be used for nuclear-powered and renewable ammonia production, respectively. Sensitivity analyses are performed for CO 2 pipeline transport distances, potential carbon capture tax credits, and clean H 2 production cost. Carbon-capturing ammonia production reduces WTG GHG emissions by 55–70% compared to conventional NG-based ammonia production methods. Nuclear-powered and renewable ammonia production almost eliminate GHG emissions since energy supply is either zero carbon or near-zero carbon. However, when $4.16–4.83 per kg is the cost assumed for clean H 2 production using state-of-the-art electrolysis technologies, the levelized costs of nuclear-powered and renewable ammonia are calculated to be $0.92–1.06 per kg NH 3 , which are approximately four times higher than the conventional NG-based ammonia production cost. The cost of CO 2 emission avoidance is estimated in the range of $266–318 per metric ton of CO 2 for nuclear-powered and renewable ammonia production. The clean H 2 production cost is the major contributor to the levelized costs of nuclear-powered and renewable ammonia production. A lower production cost, near $1 per kg H 2 , for clean H 2 is required for nuclear-powered and renewable ammonia production to be cost-competitive with conventional NG-based ammonia production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

What Questions Would a Systems Engineer Ask to Assess Systems Engineering Models as Credible

Digital Systems Engineering strategies typically call for digital Systems Engineering models to be retained in repositories and certified as an authoritative source of truth (enabling model reuse, qualification, and collaboration). In order for digital Systems Engineering models to be certified as authoritative (credible), they need to be assessed - verified and validated - and with the amount of uncertainty in the model quantified (consider reusing someone else's model without knowing the author). Due to this increasing model complexity, the authors assert that traditional human-based methods for validating, verifying, and uncertainty quantification - such as human-based peer-review sessions - cannot sufficiently establish that a digital Systems Engineering model of a complex system is credible. Digital Systems Engineering models of complex systems can contain millions of nodes and edges. The authors assert that this level of detail is beyond the ability of any group of humans - even working for weeks at a time - to discern and catch every minor model infraction. In contrast, computers are highly effective at discerning infractions with massive amounts of information. The authors suggest that a better approach might be to focus the humans at what model patterns should be assessed and enable the computer to assess the massive details in accordance with those patterns - by running through perhaps 100,000 test loops. In anticipation of future projects to implement and automate the assessment of models at Sandia National Laboratories, a study was initiated to elicit input from a group of 25 Systems Engineering experts. The authors positioning query began with - 'What questions would a Systems Engineer ask to assess Systems Engineering models for credibility?" This report documents the results of that survey.

42 ENGINEERING↗

NASA NTRS1991

Kate's Model Verification Tools

Kennedy Space Center's Knowledge-based Autonomous Test Engineer (KATE) is capable of monitoring electromechanical systems, diagnosing their errors, and even repairing them when they crash. A survey of KATE's developer/modelers revealed that they were already using a sophisticated set of productivity enhancing tools. They did request five more, however, and those make up the body of the information presented here: (1) a transfer function code fitter; (2) a FORTRAN-Lisp translator; (3) three existing structural consistency checkers to aid in syntax checking their modeled device frames; (4) an automated procedure for calibrating knowledge base admittances to protect KATE's hardware mockups from inadvertent hand valve twiddling; and (5) three alternatives for the 'pseudo object', a programming patch that currently apprises KATE's modeling devices of their operational environments.

Morgan, Steve↗

NASA NTRS1995

A method for diagnosing time dependent faults using model-based reasoning systems

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Goodrich, Charles H.↗

DOE OSTI2025

Novel Results Visualization for Dynamic PSA and New Modeling Features in EMRALD

The Event Modeling Risk Assessment Linked Diagram (EMRALD) tool, developed at the Idaho National Laboratory (INL), was designed to simplify the creation of dynamic models and support various research projects. One of the primary goals of EMRALD was to provide visual methods for modeling. EMRALD consists of two main components: a web-based user interface for model development and a solve engine for running model simulations. Over time, it has evolved to meet the diverse needs of its users. Initially, EMRALD's results were simple text outputs with final key state percentages and uncertainty bounds. However, because EMRALD utilizes a three-phase discrete event simulation and tracks the paths of each simulation run leading to a key state, there is significant potential to analyze large sets of path results data, including state paths, events, and timing. Visualizing this data meaningfully posed a challenge. To address this, a novel time-based Sankey diagram was developed. EMRALD exports results data in a format that can be opened in this Sankey viewer, allowing users to visualize paths, occurrences, events, and probability data for the entire simulation run in a single diagram. Moreover, when EMRALD was first created, there were limited tools capable of meeting its graphical requirements, many of which are no longer supported. In 2024, a new web-based interface was developed using modern graphing tools, enabling additional modeling features. This paper discusses the new dynamic PSA results visualization capability and the enhanced modeling tools available in EMRALD.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗

DOE OSTI2020

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗

NASA NTRS1997

Science Support for Space-Based Droplet Combustion: Drop Tower Experiments and Detailed Numerical Modeling

This program supports the engineering design, data analysis, and data interpretation requirements for the study of initially single component, spherically symmetric, isolated droplet combustion studies. Experimental emphasis is on the study of simple alcohols (methanol, ethanol) and alkanes (n-heptane, n-decane) as fuels with time dependent measurements of drop size, flame-stand-off, liquid-phase composition, and finally, extinction. Experiments have included bench-scale studies at Princeton, studies in the 2.2 and 5.18 drop towers at NASA-LeRC, and both the Fiber Supported Droplet Combustion (FSDC-1, FSDC-2) and the free Droplet Combustion Experiment (DCE) studies aboard the shuttle. Test matrix and data interpretation are performed through spherically-symmetric, time-dependent numerical computations which embody detailed sub-models for physical and chemical processes. The computed burning rate, flame stand-off, and extinction diameter are compared with the respective measurements for each individual experiment. In particular, the data from FSDC-1 and subsequent space-based experiments provide the opportunity to compare all three types of data simultaneously with the computed parameters. Recent numerical efforts are extending the computational tools to consider time dependent, axisymmetric 2-dimensional reactive flow situations.

Marchese, Anthony J.↗

NASA NTRS1983

A generalized computer code for developing dynamic gas turbine engine models (DIGTEM)

This paper describes DIGTEM (digital turbofan engine model), a computer program that simulates two spool, two stream (turbofan) engines. DIGTEM was developed to support the development of a real time multiprocessor based engine simulator being designed at the Lewis Research Center. The turbofan engine model in DIGTEM contains steady state performance maps for all the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. DIGTEM features an implicit integration scheme for integrating stiff systems and trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off design points and iterates to a balanced engine condition. Transients are generated by defining the engine inputs as functions of time in a user written subroutine (TMRSP). Closed loop controls can also be simulated. DIGTEM is generalized in the aerothermodynamic treatment of components. This feature, along with DIGTEM's trimming at a design point, make it a very useful tool for developing a model of a specific turbofan engine.

Daniele, C. J.↗

NASA NTRS1984

A generalized computer code for developing dynamic gas turbine engine models (DIGTEM)

Daniele, C. J.↗

DOE OSTI2023

Modeling the impact of the fuel injection strategy on the combustion and performance characteristics of a heavy-duty GCI engine

Gasoline compression ignition (GCI) is a promising strategy to achieve high thermal efficiency and low emissions with limited modifications to the conventional diesel engine hardware. It is a partially premixed concept, which derives its superiority from higher volatility and longer ignition delay of gasoline-like fuels combined with higher compression ratio typical of diesel engines. Here, the present study investigates the combustion process in a GCI engine operating with different injection strategies using computational fluid dynamics (CFD). Simulations are carried out on a single cylinder of a multi cylinder heavy-duty compression ignition engine, which operates at a compression ratio of 17:1 and an engine speed of 1038 rev/min. Two different injection strategies viz., late injection (LI), and early pilot injection (EP) are investigated to understand their impact on combustion and performance of the engine. Renormalized group (RNG) k-ε model is used to describe in-cylinder turbulence and KH RT model is used to simulate the fuel spray breakup. The developed CFD methodology is validated against relevant experimental data under a wide range of operating conditions for each injection strategy. The developed CFD methodology was found to capture the engine combustion behavior quite well. Based on the validated CFD model, the differences in the progress of combustion event for the two injection strategies is highlighted. It was found that a larger pilot fuel mass fraction results in a steeper rise in the initial heat release rate which in turn influences the transition to mixing controlled combustion. In line with the experimental data, the study showed that the late pilot injection strategy with three injection pulses, results in higher performance compared to the other conditions.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models

To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies—using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.

17 WIND ENERGY↗

DOE OSTI2013

An experimental and modeling study investigating the ignition delay in a military diesel engine running hexadecane (cetane) fuel

In an effort aimed at predicting the combustion behavior of a new fuel in a conventional diesel engine, cetane (n-hexadecane) fuel was used in a military engine across the entire speed–load operating range. The ignition delay was characterized for this fuel at each operating condition. A chemical ignition delay was also predicted across the speed–load range using a detailed chemical kinetic mechanism with a constant pressure reactor model. At each operating condition, the measured in-cylinder pressure and predicted temperature at the start of injection were applied to the detailed n-hexadecane kinetic mechanism, and the chemical ignition delay was predicted without any kinetic mechanism calibration. The modeling results show that fuel–air parcels developed from the diesel spray with an equivalence ratio of 4 are the first to ignite. The chemical ignition delay results also showed decreasing igntion delays with increasing engine load and speed, just as the experimental data revealed. At lower engine speeds and loads, the kinetic modeling results show the characteristic two-stage negative temperature coefficient behavior of hydrocarbon fuels. However, at high engine speeds and loads, the reactions do not display negative temperature coefficient behavior, as the reactions proceed directly into high-temperature pathways due to higher temperatures and pressure at injection. A moderate difference between the total and chemical ignition delays was then characterized as a phyical delay period that scales inversely with engine speed. This physical delay time is representative of the diesel spray development time and is seen to become a minority fraction of the total igntion delay at higher engine speeds. In addition, the approach used in this study suggests that the ignition delay and thus start of combustion may be predicted with reasonable accuracy using kinetic modeling to determine the chemical igntion delay. Then, in conjunction with the physical delay time (experimental or modeling based), a new fuel’s acceptability in a conventional engine could be assessed by determining that the total ignition delay is not too short or too long.

30 DIRECT ENERGY CONVERSION↗

NASA NTRS2019

Multipoint Variable Cycle Engine Design Using Gradient-based Optimization

Supersonic aircraft are challenging to optimally design due to the widely varying constraints and flight conditions they experience. Additionally, a large number of disciplinary subsystems must be considered due to highly complex design requirements. One subsystem that has a major effect on overall performance is the engine. In this work, we construct a supersonic mixed-flow variable cycle engine and perform multipoint gradient-based optimization using this model. We see that the operational variables allow the optimizer to tailor performance at each individual flight condition, leading to better overall performance. To simulate airframe integration constraints, we run successive optimizations with increasingly restrictive inlet areas and see decreases in engine performance. This work is part of a larger effort to incorporate engine design into aero-thermal-mission optimization of a supersonic aircraft.

Cycle analysis↗

NASA NTRS2010

Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations

This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed. The other two types of algorithms being deployed include a "nile-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rule-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions), a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," can be found in. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to an aggregation of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).

Martin, Rodney Alexander↗

DOE OSTI2018

Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation

3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user who may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations. This study used ANSYS® Forte, Version 17.2, and the built-in G-equation model, to investigate two tuning constants that influence flame propagation in 3D CFD SI engine simulations: the stretch factor coefficient, Cms and the flame development coefficient, Cm2. After identifying several Cm2-Cms pairs that matched experimental data at one operating conditions, simulation results showed that engine models that used different Cm2-Cms sets predicted similar combustion performance, when the spark timing, engine load, and engine speed were changed from the operating condition used to validate the CFD simulation. A dramatic shift was observed when engine speed was doubled, which suggested that the flame stretch coefficient, Cms, had a much larger influence at higher engine speeds compared to the flame development coefficient, Cm2. Therefore, the Cm2-Cms sets that predicted a higher turbulent flame under higher in-cylinder pressure and temperature increased the peak pressure and efficiency. This suggest that the choice of the Cm2-Cms will affect the G-equation-based simulation accuracy when engine speed increases from the one used to validate the model. As a result, for the less-experienced CFD user and in the absence of enough experimental data that would help retune the tuning parameters at various operating conditions, the purpose of a good G-equation-based 3D engine simulation is to guide and/or complement experimental investigations, not the other way around. Only a truly-predictive simulation that fully couples the turbulence/chemistry equations can help reduce the amount of experimental work.

42 ENGINEERING↗

NASA NTRSDate not supplied

Preliminary Dynamic Modeling of the Quarter-Scale Distributed Electric Propulsion Aircraft

This paper describes the early-stage modeling of a quarter-scale distributed electric propulsion aircraft, based on the SUbsonic Single Aft eNgine (SUSAN) Electrofan, a transformative concept aircraft for which a model exists. The full-scale 180 passenger SUSAN concept has a single turbofan engine in the tail that both produces thrust and provides electrical power to 16 electric fans distributed across the wings utilizing a series/parallel hybrid architecture. The quarter-scale version would have an internal combustion piston engine to provide power to 17 electric fans–16 on the wings, one in the tail–in a series hybrid configuration, and no vertical or horizontal stabilizers. It would also have a reduced flight envelope in terms of both altitude and speed. The initial modeling approach is to scale down the original airframe model to capture the dynamic behavior of a much smaller aircraft, albeit with an empennage. The original powertrain model is then replaced with one representing the physical components of that of the quarter-scale vehicle. This powertrain model is suitable for control design and analysis, and the fully integrated, although preliminary, aircraft model allows flight simulator testing and evaluation. Results from simulations are presented.

electrified aircraft propulsion↗

NASA NTRSDate not supplied

Preliminary Dynamic Modeling of the Quarter-Scale Distributed Electric Propulsion Aircraft

This presentation describes the early-stage modeling of a quarter-scale distributed electric propulsion aircraft, based on the SUbsonic Single Aft eNgine (SUSAN) Electrofan, a transformative concept aircraft for which a model exists. The full-scale 180 passenger SUSAN concept has a single turbofan engine in the tail that both produces thrust and provides electrical power to 16 electric fans distributed across the wings utilizing a series/parallel hybrid architecture. The quarter-scale version would have an internal combustion piston engine to provide power to 17 electric fans–16 on the wings, one in the tail–in a series hybrid configuration, and no vertical or horizontal stabilizers. It would also have a reduced flight envelope in terms of both altitude and speed. The initial modeling approach is to scale down the original airframe model to capture the dynamic behavior of a much smaller aircraft, albeit with an empennage. The original powertrain model is then replaced with one representing the physical components of that of the quarter-scale vehicle. This powertrain model is suitable for control design and analysis, and the fully integrated, although preliminary, aircraft model allows flight simulator testing and evaluation. Results from simulations are presented.

electrified aircraft propulsion↗